Janne Kim Gitmark

Identifying Rocky Seabed Using GIS-Modeled Predictor Variables

Mapping the seabed along the Norwegian coast is costly and time consuming. Hence, finding a modeling method to separate rocky seabed from other substrate types will provide digital maps that may be used to develop cost-effective sampling designs to predict species and habitat distribution. Our approach was to use geophysical data that were quantitative and objectively defined, generalized additive models (GAMs), and Akaike information criterion (AIC) to develop statistical models and select among them. We found that slope, terrain curvature, wave exposure, and depth predicted rocky seabed occurrence with a high degree of certainty.

A snap shot of the short-term response of crustaceans to macrophyte detritus in the deep Oslofjord

A test deployment of a time-lapse camera lander in the deep Oslofjord (431 m) was used to obtain initial information on the response of benthic fauna to macroalgal debris. Three macroalgal species were used on the lander baited plate: Fucus serratus, Saccharina latissima and Laminaria hyperborea and observed during 41.5 hours. The deep-water shrimp Pandalus borealis were attracted to the macroalgae rapidly (3 min after the lander reached the seafloor), followed by amphipods. Shrimp abundances were significantly higher in areas covered by macroalgae compared to the adjacent seafloor and the number of shrimp visiting the macroalgae increased with time. Amphipods arrived 13 hours later and were observed mainly on decaying L. hyperborea. The abundance of amphipods on L. hyperborea increased rapidly, reaching a peak at 31 h after deployment. These initial observations suggest that debris from kelp forests and other macroalgal beds may play an important role in fuelling deep benthic communities in the outer Oslofjord and, potentially, enhance secondary production of commercial species such as P. borealis.